It has been shown in SSL that the conditional probability distribution varies smoothly along the manifold of its marginal distribution [1]}. Here, we assume that similar conclusion holds for our case, i.e, the model should output smooth predictions for data points in-between adjacent snippets. Besides, such property is consistent with the natural smoothness of videos.
Specifically, we first normalize the snippet logit scores \(S\)  with a \(\operatorname{Softmax}\)  operation as,
\(\small \begin{aligned}P = \operatorname{Softmax}(S)\end{aligned}\) 
